diff --git a/docs/source/en/quantization/torchao.md b/docs/source/en/quantization/torchao.md
index ac9fbc7ca72..164f6851f32 100644
--- a/docs/source/en/quantization/torchao.md
+++ b/docs/source/en/quantization/torchao.md
@@ -65,13 +65,14 @@ pip install --upgrade torchao transformers
Stable Release from the PyTorch index
+
```bash
pip install torchao --index-url https://download.pytorch.org/whl/cu126 # options are cpu/cu118/cu126/cu128
```
-If your torcha version is below 0.10.0, you need to upgrade it, please refer to the [deprecation notice](#deprecation-notice) for more details.
+If your torchao version is below 0.10.0, you need to upgrade it, please refer to the [deprecation notice](#deprecation-notice) for more details.
## Quantization examples
@@ -88,6 +89,7 @@ We'll show examples for recommended quantization methods based on hardwares, e.g
### H100 GPU
+
```py
import torch
from transformers import TorchAoConfig, AutoModelForCausalLM, AutoTokenizer
@@ -148,6 +150,7 @@ print(tokenizer.decode(output[0], skip_special_tokens=True))
### A100 GPU
+
```py
import torch
from transformers import TorchAoConfig, AutoModelForCausalLM, AutoTokenizer
@@ -215,6 +218,7 @@ print(tokenizer.decode(output[0], skip_special_tokens=True))
### CPU
+
```py
import torch
from transformers import TorchAoConfig, AutoModelForCausalLM, AutoTokenizer
@@ -385,6 +389,7 @@ To avoid arbitrary user code execution, torchao sets `weights_only=True` in [tor
+
```py
# don't serialize model with Safetensors
output_dir = "llama3-8b-int4wo-128"
@@ -392,6 +397,7 @@ quantized_model.save_pretrained("llama3-8b-int4wo-128", safe_serialization=False
```
+
```py
# don't serialize model with Safetensors
USER_ID = "your_huggingface_user_id"